Analyzing complex survey data
By: Eun Sul Lee, Ronald N. Forthofer.
Contributors: Forthofer, Ron N., 1944-
Edition: 2nd ed.
Series: Quantitative applications in the social sciences ;; vol. 71; Sage university papers series.; no. 07-71.
Publisher: Sage Publications
Published: 2006
Place of publication: Thousand Oaks, Calif
Language: eng
Number of pages: 91
Subjects: Mathematical statistics.; Social surveys -- Statistical methods.
Description: In this introduction to the different ways of analysing complex survey data, the authors consider new analytical approaches review new software and introduce a model-based analysis that can be used for well-designed and relatively small-scale social surveys.
Notes: Includes bibliographical references and index.
Table of contents: title: Introduction; title: Sample design and survey data; title: Types of sampling; title: The nature of survey data; title: A different view of survey data; title: Complexity of analyzing survey data; title: Adjusting for differential representation: the weight; title: Developing the weight by poststratification; title: Adjusting the weight in a followup survey; title: Assessing the loss or gain in precision: the design effect; title: The use of sample weights for survey data analysis; title: Strategies for variance estimation; title: Replicated sampling: a general approach; title: Balanced repeated replication; title: Jackknife repeated replication; title: The bootstrap method; title: The Taylor series method (linearization); title: Preparing for survey data analysis; title: Data requirements for survey analysis; title: Importance of preliminary analysis; title: Choices of the method for variance estimation; title: Available computing resources; title: Creating replicate weights; title: Searching for appropriate models for survey data analysis; title: Conducting survey data analysis; title: A strategy for conducting preliminary analysis; title: Conducting descriptive analysis; title: Conducting linear regression analysis; title: Conducting contingency table analysis; title: Conducting logistic regression analysis; title: Other logistic regression models; title: Design-based and model-based analysis*; title: Concluding remarks.